Abstract
Both objective and subjective determinants of success and failure in the labour market are examined. The objective indicators are the employment situation and the wages earned; the subjective measures concern work values and the realization of these values, and job satisfaction. Almost three quarters of all graduates were in “relevant” employment, that is, held a job that matched both their level and field of higher education. The shares of unemployed, “vertically mismatched” and/or “horizontally mismatched” differ by country, by level and field of education, and by personal or higher education characteristics. Large wage differences persist according to gender, field of study and type of employment contract. The analyses distinguished three types of work orientations: Career and status orientation; professional/innovative orientation; and a social orientation. Males scored higher than females in most countries on the career dimension, while females scored clearly higher than males on the professional/innovative and especially the social dimension in all countries. Almost two thirds could be classified as winners on the professional/innovative dimension (succeeded in realizing the underlying values), whereas just over one fifth of graduates were winners on the career dimension. More than two thirds of all graduates reported that they were satisfied with their current work. Those who are winners on the professional/innovative dimension are most often satisfied with their job.
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Notes
- 1.
A job analyst might do a better job, but self-assessment is the most economic method and it is probably as valid as job analyses because the content of jobs change faster than the available instruments for standard classifications of jobs.
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- 3.
See further definition in Appendix 1.
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The proportion of vertical mismatch among this group does not depend on whether the degree was obtained shortly after the reference year or later, around the time of the survey.
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Based on a mixture of ISCED broad and narrow fields of study.
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Based on an extended model including controls for number of months with unemployment experience and the number of times unemployed. These variables are not included in the other models.
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The respondents gave information on gross monthly wages in their main job. The monthly wage has been converted to hourly wages by correcting for contract working hours.
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We have estimated two models. In model 1, we have included gender, age, relative grades, level of education, field of study, vocationally oriented study, prestigious study programme, relevant work experience before and after graduation, working hour, parents with higher education and position in students or other voluntary organisations is used in model 1. In model 2, we have in addition to the variables already mentioned mismatch variables and a variable indicating whether the job is permanent or not. The regression coefficients and the method for converting the coefficients into percentage wage increments are available on request from the authors.
- 9.
The educational level refers to the level in 1999/2000. We have not taken into account whether the graduate had finished a second-level or PhD/specialist degree during the years from 2000 to the time of the survey in the column “observed”. However, in the column “estimated”, information on further education is used as explanatory variables.
- 10.
Percentage of variance based on rotation sums of squared loadings.
- 11.
Farag and Allen (2003) take the former view, because these values are not related to work as such. However, these kinds of values may also be interpreted as “post-modern self-expression” (and as such intrinsic values) to satisfy “higher-order” psychological needs.
- 12.
Most of the respondents found at least one of the items connected to one of these three dimensions important or very important. Of those who had answered all the questions concerning work values, 82% found the career values important (at least one of the career items), 97% found the social values dimension (at least one of the items) important and 98% found the professional/innovative dimension important. Only 0.2% did not find any of the dimensions important, and 79% found all the three dimensions important.
- 13.
These gender differences are statistically significant after control for relevant background variables (detailed results available on request from the authors), and based on such regressions, the probability of being a career winner is estimated to be 4% points less among females than males (the same as in bivariate relationship in Fig. 8.21).
- 14.
Additional analysis also shows that the social values dimension is particularly important for this group.
- 15.
Detailed results available on request from the authors.
- 16.
In the regressions on which the estimates are based, we have also controlled for wages. This reduces the effect of being mismatched on the career dimension but has little impact on the other two dimensions.
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Appendices
Appendix 1: Definition of Mismatch
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1.
Employed with relevant work, that is, persons not belonging to one of the four groups below.
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Horizontally mismatched (and not vertically mismatched).This refers to persons who gave an answer to the question “What field of study do you feel is most appropriate for this work?” that indicated that their work did not correspond to their own or a related field.
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Vertically mismatched (and not horizontally mismatched). This group is overeducated (overqualified) and the definition refers to those who gave an answer to the question “What type of education do you feel is most appropriate for this work?” (“type” refers to “level” according to the response options in the questionnaire) that indicated a level below their educational level. We have taken into account the fact that some have acquired a higher educational level after their graduation in 1999/2000 (as masters or second-level graduates or PhDs/specialists). First-level graduate/bachelors who had taken further education and have become masters or second-degree graduates and hold a job that corresponds to the first level/bachelor level are regarded as vertically mismatched and vice versa for master or second-degree graduates who have obtained a PhD/specialist degree.
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Both vertically and horizontally mismatched.
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Unemployed. This refers to respondents who answered that they were not currently employed and who reported that they had actively tried to obtain paid work in the past four weeks, or who reported that they were awaiting the results of earlier job applications.
Appendix 2: The Effect on Wages of Gender, Grades, Level of Education, Field of Study, Mismatch and Type of Job Contract, Percentage
All countries | Italy | Spain | France | Austria | Germany | Netherlands | UK | Finland | Norway | Czech rep. | Switzerland | Belgium | Estonia | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Gender | ||||||||||||||
Females/males | –9.6 | –11.9 | –7.3 | –12.4 | –10.5 | –10.7 | –4.2 | –10.4 | –10.3 | –9.9 | –10.4 | –4.8 | –7.5 | –15.0 |
Grades | ||||||||||||||
Grades above average/average and below | 3.1 | 3.7 | 8.7 | 3.4 | 3.6 | 3.8 | 1.7 | 7.8 | –0.3 | 4.4 | 1.5 | 2.2 | –1.1 | 7.5 |
Level of education | ||||||||||||||
First level/second level | –10.3 | –3.6 | –14.1 | –15.5 | 6.2 | –8.1 | –16.8 | –2.9 | –19.8 | –16.4 | –8.1 | –5.3 | –6.1 | –2.5 |
Field of study | ||||||||||||||
Education/social science | –4.3 | –10.2 | 8.4 | –4.4 | –5.5 | –5.2 | –6.5 | 0.8 | 1.4 | –9.1 | –14.7 | 3.4 | –11.9 | –8.0 |
Human/social science | –6.2 | –3.5 | –1.1 | 3.8 | –10.4 | –9.6 | –9.2 | –6.7 | –1.4 | –15.1 | –20.9 | –2.9 | –10.4 | –8.7 |
Law/social science | –0.1 | –12.1 | –1.2 | 6.8 | –4.7 | –13.7 | 8.7 | 2.4 | 24.8 | –7.3 | –0.3 | 4.0 | 0.9 | 21.8 |
Business/social science | 11.8 | 7.0 | 2.7 | 21.0 | 16.7 | 26.4 | 7.1 | 15.2 | 9.3 | 18.5 | 5.8 | 8.6 | 3.9 | 26.4 |
Computing/social science | 13.7 | 11.2 | 11.6 | 4.2 | 21.1 | 10.2 | 8.7 | –5.8 | 20.5 | 4.0 | 8.4 | 0.0 | 2.8 | 27.4 |
Science rest/social science | 1.0 | 6.5 | –1.6 | 13.1 | 4.0 | 5.0 | –5.4 | 8.2 | –1.8 | –7.2 | –12.0 | –4.1 | 0.4 | –8.9 |
Engineering/social science | 7.8 | 9.6 | 15.6 | 22.3 | 8.7 | 11.7 | 1.5 | 10.0 | 16.1 | 0.6 | –5.8 | –2.9 | 1.5 | 19.1 |
Agriculture/social science | –10.6 | –28.3 | 0.2 | –5.0 | –1.2 | –4.6 | –2.6 | –18.6 | –5.6 | –16.6 | –21.4 | –9.3 | –7.5 | –25.2 |
Health/social science | –0.3 | 8.2 | 7.3 | 7.4 | 7.9 | 4.7 | –0.9 | 12.5 | 2.0 | –4.2 | –12.7 | –4.8 | –1.1 | –9.7 |
Service/social science | 0.7 | 15.5 | 16.2 | 13.9 | –8.3 | 5.2 | 1.3 | –0.9 | 4.8 | –7.5 | –7.2 | –18.5 | –18.0 | –9.0 |
Graduated from a prestigious education | 5.4 | 5.4 | 4.1 | 7.5 | –0.6 | 3.3 | 0.0 | 8.7 | 2.7 | 5.4 | 2.1 | 2.6 | 5.5 | 11.9 |
Further education | ||||||||||||||
Master as further education | 12.1 | 0.5 | 11.7 | 16.2 | –0.2 | 19.1 | 15.6 | 3.7 | 27.7 | 13.1 | 6.0 | 9.0 | 9.1 | 5.8 |
PhD as further education | 8.7 | 11.3 | 0.2 | 9.1 | 11.9 | 7.3 | 4.9 | 4.5 | 11.1 | 6.1 | 9.2 | 1.6 | 11.5 | 6.1 |
Other further education | 1.7 | –0.4 | 2.3 | 1.7 | 1.8 | 5.7 | 1.2 | 5.7 | 0.5 | –0.3 | –0.5 | 2.7 | 0.7 | 5.1 |
Mismatch | ||||||||||||||
Horizontal mismatch/relevant job | 1.6 | –0.4 | –7.6 | –2.7 | 3.6 | 1.4 | 2.2 | –0.5 | 5.4 | 11.9 | 5.0 | 3.8 | –1.1 | 7.5 |
Vertical mismatch /relevant job | –11.6 | –3.9 | –14.7 | –12.6 | –11.8 | –6.8 | –13.3 | –15.8 | –17.0 | –6.2 | –13.2 | –4.0 | –11.3 | –3.6 |
Horizontal and vertical mismatch /relevant job | –11.4 | –6.3 | –9.3 | –12.1 | –10.4 | –17.1 | –10.3 | –9.7 | –8.1 | –18.5 | 0.7 | –10.4 | –0.5 | 7.0 |
Type of contract | ||||||||||||||
Permanent job /temporary job | 13.0 | 13.4 | 10.3 | 22.9 | 10.1 | 18.7 | 10.5 | 10.7 | 15.5 | 11.7 | 14.5 | 20.2 | 16.1 | –1.6 |
Country (compared to the Netherlands) | –38.1 | –30.8 | –9.1 | –8.9 | 14.4 | Ref. cat. | 4.3 | –8.7 | 8.3 | –48.7 | 21.9 | 2.7 | –38.6 |
Appendix 3: Definition of Winners and Losers According to the Graduates’ Response to the Questions on Work Values and Job Characteristics (Realisation of Work Values)
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1.
For all the ten work values items, a variable was created according to whether or not the item was important for the respondent. Value 4 (important) + 5 (very important) on a scale from 1 to 5 were recoded as important (assigned value 1, else 0).
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2.
Losers and winners variables were created for each of the ten items of job characteristics (to what extent the work values apply to current work). If the respondent had value 1 on the variable mentioned above, that is, finds the item important, and value 1 or 2 on corresponding item for job characteristics, he/she was coded as a loser on this variable. If the respondent finds the item important and value 4 or 5 on corresponding item for job characteristics, he/she was coded as a winner on this variable.
From the results of the factor analyses of work values, we knew that the work values clustered into three dimensions, allowing us to identify three groups that are career oriented, professional oriented and “social values” oriented. The next step was then:
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3.
Three new variables were created “lose/win-career”, “lose/win-innovative” and “lose/win-social”, all with three values; value 1=lose, value 2=win, value 9=neutral, the latter as the reference category to be used in multinomial regression. These variables were created according to the following:
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Based on step 1 and 2, a respondent was categorised as a winner on the “lose/win-career” variable if she/he had value 1 on (at least) two of the three job-characteristic variables “win-earnings”, “win-career-prospects” or “win-social-status”, and she/he was categorised as “loser” on the “lose/win-career” variable if he/she had value 1 on (at least) two of the variables “lose-earnings”, “lose-career-prospects” or “lose-social-status”. Else, the respondent was categorised as neutral.
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Likewise values were assigned on the “lose/win-innovative” variable according to the response to the three job-characteristic variables that concern autonomy, new challenges or learn new things.
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Finally, values were assigned in the same way on the “lose/win-social” variable according to the respondent’s answers to the four job-characteristic variables that concern job security, leisure activities, do something useful for society and combine work and family. (The coding of “lose/win-social” variable was based on the respondent being a winner/loser, respectively, on three of the four items covered by this dimension.)
Multinomial logistic regressions for each of the three winner situations (dimensions) were run. For each of the regressions, respondents who found one of the three (four) items connected to the particular dimension important were selected.
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Støren, L.A., Arnesen, C.Å. (2011). Winners and Losers. In: Allen, J., van der Velden, R. (eds) The Flexible Professional in the Knowledge Society. Higher Education Dynamics, vol 35. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1353-6_8
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